Aid Effectiveness and Women’s Empowerment: Practices of Governance in the Funding of International Development
Bibliographic record
Abstract
Although the empowerment of women is a prominent goal in international development, feminist development professionals, activists, and scholars remain deeply dissatisfied with the limited extent to which women's empowerment is actually achieved. Their experiences and analyses raise questions about the connections and disjunctions between discourse, institutional practices, and everyday life. A major effort to reform development aid guided by the Paris Declaration on Aid Effectiveness raises new questions about the place of gender in development practice. Drawing on recently conducted research on women and development in Kyrgyzstan and using a range of institutional texts, we interrogate how development professionals and activists engage with the aid effectiveness discourse. Our analytic approach, institutional ethnography, shares with work on governmentality an empirical focus on practices undertaken by diversely situated people and how these practices constitute a particular field of action. Institutional ethnography directs analytic attention to the operation of texts as local and translocal coordinators of people's everyday activities. The product of this coordinated work is what we call, in this case, the development institution. For those concerned about women and development, we see the usefulness of making visible how global governance is accomplished in both enactments of and resistance to institutional practices, but in ways that do not necessarily benefit women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.049 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".